最核心的内容,就是作者提出的Cross-Image Attention。这个东西是什么呢?请看下图: 图2 我们简单总结一下,给定structure image和一个appearance image,我可以令K,V是Appearance Image,Q是structure image,然后他们做常规的Self-attention操作,可以发现,两张不同的图,长颈鹿和斑马的语义是能够对应起来的,比如脖子对脖子,...
Specifically, given a pair of images -- one depicting the target structure and the other specifying the desired appearance -- our cross-image attention combines the queries corresponding to the structure image with the keys and values of the appearance image. This operation, when applied during ...
ComfyUI_CrossImageAttention是一种基于注意力机制的图像生成方法,它可以在给定外观图和结构的前提下,生成具有一致结构和外观的图。该方法的主要思想是通过计算输入图像与预训练模型之间的相似性,将注意力集中在与输入图像最相似的部分,从而实现图像的生成。 在qkv层面,ComfyUI_CrossImageAttention的工作过程如下: 1. ...
相比于直接text2image生成,text-guided editing要求原来图像绝大部分区变化不大,目前的方法需要用户指定mask来引导生成。 本文发现cross-attention对于image的布局控制很重要。 目前已有的纯text-guided的editing(text2live)text2live,目前只能修改图片的纹理(外观),不能修改复杂的实体结构,比如把自行车换成一辆车。并且,他...
In order to tackle these challenges, we propose a noveluncertain area attention and cross-image context extraction network for accuratepolyp segmentation, which consists of the uncertain area attention module(UAAM), the cross-image context extraction module (CCEM), and theadaptive fusion module (AFM...
Official Pytorch implementation of Dual Cross-Attention for Medical Image Segmentation - gorkemcanates/Dual-Cross-Attention
Image-text Cross-modal Matching Method Based on Stacked Cross Attention Cross-modal matching of image-text is an important task in the intersection of computer vision and natural language processing. However, traditional image-... HongbinWANG,ZhiliangZHANG,HuafengLI - 《Journal of Signal Processing》...
Code has been made available at: (https://github.com/kuanghuei/SCAN).doi:10.1007/978-3-030-01225-0_13Kuang-Huei LeeXi ChenGang HuaHoudong HuXiaodong HeSpringer, ChamK. Lee, X. Chen, G. Hua, H. Hu, and X. He. Stacked cross attention for image-text matching. ECCV, 2018....
To address issues such as instability during the training of Generative Adversarial Networks, insufficient clarity in facial structure restoration, inadequate utilization of known information, and lack of attention to color information in images, a Cross-Attention Restoration Network is proposed. Initially,...
co-attention classifier由三个模块组成,分别是传统的分类器网络,以及一个共注意力网络和一个对比共注意力网络,整个网络框架如下图所示。三个模块为串联排列,首先是利用传统分类器进行分类训练,之后用提取到的特征训练了一个共注意力模块,用提取到的共注意力特征训练分类器对共享语义信息的分类敏感性,在共注意特征的...